Combined effects of maternal periconceptional environmental exposures and infant cardiac transcription factor polymorphisms on congenital heart disease risk

Background Congenital heart disease (CHD) is a leading cause of neonatal morbidity and mortality, with a complex aetiology involving genetic and environmental factors. Cardiac transcription factors, such as NKX2.5, GATA4 and TBX5, are essential for heart development, and their gene polymorphisms may contribute to CHD. Additionally, maternal periconceptional environmental exposures may influence CHD risk. Limited studies explore gene–gene and gene–environment interactions in CHD pathogenesis.Methods A hospital-based case-control study analyzed 585 CHD cases and 600 controls. Associations between transcription factor gene polymorphisms, maternal environmental exposures and CHD risk were assessed using logistic regression, multiplicative interaction models and model-based multifactor dimensionality reduction.Results Several transcription factor gene polymorphisms were significantly associated with CHD risk. Specifically, NKX2.5 (rs118026695), GATA4 (rs12458) and TBX5 (rs11067101, rs6489956) increased CHD risk, while NKX2.5 (rs703752) and GATA4 (rs4841588, rs904018) reduced risk. Gene–gene interactions among these loci further modulated CHD risk. Maternal environmental factors, such as gestational diabetes, pre-gestational diabetes, adverse pregnancy history, certain medications and lifestyle factors, were associated with higher CHD risk, certain gene–environment interactions showed suggestive associations with CHD risk, with some combinations reaching statistical significance prior to multiple testing correction.Conclusion Infant NKX2.5, GATA4 and TBX5 gene polymorphisms significantly affect CHD risk, and maternal periconceptional environmental exposures may further influence this risk through certain gene–environment combinations. These findings provide insights into CHD aetiology and highlight the need for preventive strategies. Further studies are necessary to validate these results and clarify underlying mechanisms.